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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

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Data Visualization and Visual Analytics: Seeing the World of Data

Sisense

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. One of the downsides of the role that data now plays in the modern business world is that users can be overloaded with jargon and tech-speak, which can be overwhelming.

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The Benefits, Challenges and Risks of Predictive Analytics for Your Application

Insight Software

In this modern, turbulent market, predictive analytics has become a key feature for analytics software customers. Predictive analytics refers to the use of historical data, machine learning, and artificial intelligence to predict what will happen in the future.

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A Complete Guide to Data Analytics

Astera

Data Mining : Sifting through data to find relevant information. Statistical Analysis : Using statistics to interpret data and identify trends. Predictive Analytics : Employing models to forecast future trends based on historical data. This includes changes in data meaning, data usage patterns, and context.

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You Can Have Advanced Analytics AND Augmented!

ElegantJ BI

Business users with average skills can use natural language processing (NLP) to ask a question and get a simple answer, providing insight into data integrated from data warehouses and disparate data sources across the business landscape. Users can test theories and hypothesize without risk and share data across teams.

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You Can Have Advanced Analytics AND Augmented!

ElegantJ BI

Business users with average skills can use natural language processing (NLP) to ask a question and get a simple answer, providing insight into data integrated from data warehouses and disparate data sources across the business landscape. Users can test theories and hypothesize without risk and share data across teams.

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Data Science vs Data Analytics: Key Differences

Astera

Data science covers the complete data lifecycle: from collection and cleaning to analysis and visualization. Data scientists use various tools and methods, such as machine learning, predictive modeling, and deep learning, to reveal concealed patterns and make predictions based on data.